plot.miSum: Plot 'miSum'

In bmcclintock/momentuHMM: Maximum Likelihood Analysis of Animal Movement Behavior Using Multivariate Hidden Markov Models

Plot miSum

Description

Plot the fitted step and angle densities over histograms of the data, transition probabilities as functions of the covariates, and maps of the animals' tracks colored by the decoded states.

Usage

## S3 method for class 'miSum'
plot(
  x,
  animals = NULL,
  covs = NULL,
  ask = TRUE,
  breaks = "Sturges",
  hist.ylim = NULL,
  sepAnimals = FALSE,
  sepStates = FALSE,
  col = NULL,
  cumul = TRUE,
  plotTracks = TRUE,
  plotCI = FALSE,
  alpha = 0.95,
  plotStationary = FALSE,
  plotEllipse = TRUE,
  ...
)

Arguments

x	Object miSum (as return by MIpool)
animals	Vector of indices or IDs of animals for which information will be plotted. Default: NULL ; all animals are plotted.
covs	Data frame consisting of a single row indicating the covariate values to be used in plots. If none are specified, the means of any covariates appearing in the model are used (unless covariate is a factor, in which case the first factor appearing in the data is used).
ask	If TRUE, the execution pauses between each plot.
breaks	Histogram parameter. See hist documentation.
hist.ylim	Parameter ylim for the step length histograms. See hist documentation. Default: NULL ; the function sets default values.
sepAnimals	If TRUE, the data is split by individuals in the histograms. Default: FALSE.
sepStates	If TRUE, the data is split by states in the histograms. Default: FALSE.
col	Vector or colors for the states (one color per state).
cumul	If TRUE, the sum of weighted densities is plotted (default).
plotTracks	If TRUE, the Viterbi-decoded tracks are plotted (default).
plotCI	Logical indicating whether to include confidence intervals in natural parameter plots (default: FALSE)
alpha	Significance level of the confidence intervals (if plotCI=TRUE). Default: 0.95 (i.e. 95% CIs).
plotStationary	Logical indicating whether to plot the stationary state probabilities as a function of any covariates (default: FALSE)
plotEllipse	Logical indicating whether to plot error ellipses around imputed location means. Default: TRUE.
...	Additional arguments passed to graphics::plot and graphics::hist functions. These can currently include asp, cex, cex.axis, cex.lab, cex.legend, cex.main, legend.pos, and lwd. See par. legend.pos can be a single keyword from the list “bottomright”, “bottom”, “bottomleft”, “left”, “topleft”, “top”, “topright”, “right”, and “center”. Note that asp and cex only apply to plots of animal tracks.

Details

The state-dependent densities are weighted by the frequency of each state in the most probable state sequence (decoded with the function viterbi for each imputation). For example, if the most probable state sequence indicates that one third of observations correspond to the first state, and two thirds to the second state, the plots of the densities in the first state are weighted by a factor 1/3, and in the second state by a factor 2/3.

Examples

## Not run: 
# Extract data from miExample
obsData <- miExample$obsData

# error ellipse model
err.model <- list(x= ~ ln.sd.x - 1, y =  ~ ln.sd.y - 1, rho =  ~ error.corr)

# Fit crawl to obsData
crwOut <- crawlWrap(obsData,theta=c(4,0),fixPar=c(1,1,NA,NA),
                    err.model=err.model)
                    
# Fit four imputations
bPar <- miExample$bPar
HMMfits <- MIfitHMM(crwOut,nSims=4,poolEstimates=FALSE,
                   nbStates=2,dist=list(step="gamma",angle="vm"),
                   Par0=bPar$Par,beta0=bPar$beta,
                   formula=~cov1+cos(cov2),
                   estAngleMean=list(angle=TRUE),
                   covNames=c("cov1","cov2"))
                   
# Pool estimates
miSum <- MIpool(HMMfits)
plot(miSum)

## End(Not run)

bmcclintock/momentuHMM documentation built on Oct. 26, 2022, 1 a.m.